code: def test_blip2_flant5xxl(self):
      # loads BLIP2-FLAN-T5XXL caption model,
      model, vis_processors, _ = load_model_and_preprocess(
          name="blip2_t5",
          model_type="pretrain_flant5xxl",
          is_eval=True,
          device=device,
      )
  
      # preprocess the image
      # vis_processors stores image transforms for "train" and "eval" (validation / testing / inference)
      image = vis_processors["eval"](raw_image).unsqueeze(0).to(device)
  
      # generate caption
      caption = model.generate({"image": image})
  
      assert caption == ["the merlion statue in singapore"]
  
      # generate multiple captions
      captions = model.generate({"image": image}, num_captions=3)
  
      assert len(captions) == 3
  
file_path: lavis/tests/models/test_blip2.py
imports: import pytest
  import torch
  from lavis.models import load_model, load_model_and_preprocess
  from PIL import Image
label_desc: Use image node_id 6 for calling the TestBlip2 obj's underlying member method code with example usage: obj.test_blip2_flant5xxl() without return types